Scraping Projects

Web scraping

I need this source to be scraped https://light-building.messefrankfurt.com/frankfurt/en/exhibitor-search.html?page=1&pagesize=90 I have the attached the sample what needed to be scraped i need the output in excel format Budget is fixed

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Building database of owners by web scraping

I have been working with DeepSeek to extract data from the web site tuscasasrurales.com. The data I need is shown on the attached file Granada.png. Some of this data requires a link to be clicked as shown in the uploaded file Tuscasasrurales.png. Email addresses have to be obtained by visiting the website (if there is one). Where no data is available, leave blank. I have been trying to extract the data province by Spanish province. To get a list by province, enter the site and add the name of the province in the search box e.g Granada which returns 304 entries. Although DeepSeek was unable to get all the info I wanted it has given me a python script which will do the job. I have uploaded this. It does not include the fields Bedrooms and Bathrooms which I would also like included. Can you do this work and how much would you charge? There are initially 10 provinces with an average of +/- 200 entries in each. Thanks - Allan

Scraping of Website database information

Require a straightforward web-scraping project to extract publicly available database records from a website. Gather complete contact details including names, email addresses, phone numbers and physical addresses. Deliver clean, deduplicated structured data (CSV or JSON) with clear field mapping. Ensure respectful, lawful scraping practices, include brief documentation of methods, sample code and any dependencies. Bid with estimated timeline and fixed price.

Data Scraping

I am seeking an adept data scraper to extract comprehensive information from a specified Shopify blog and compile it into a structured spreadsheet for seamless importation into a WordPress platform. The required data includes the original blog URL, publication date, URL link to the article's image, article title, and the full content of each article. The task involves approximately 174 articles, necessitating meticulous attention to detail and accuracy. Your expertise in data extraction and formatting will be invaluable for this project. the url is: https://kingsnqueens.com/blogs/news. Thank you for your interest!

PDF Scraping

Hi, I need to scrape Item# & HT# from first table and "Item and Piece# together" and HT# from 2nd table. I also need Spool# given on the bottom right corner. Sample PDF is attached. There are around 600 pages. This is not a manual data entry job. I need coders to extract data programmatically within few hours.

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Weekly Scrape to CSV / Google Doc

We need a scraper building. The site ot be scraped is https://www.jesuk.com/ We have the login to enable prices to be seen, this will be shared once the project is awarded. The scraper needs to run daily and populate a database with a front end where we can see: SKU Product Title Price - highlighting Price changes New Products added Products that no longer exist It should show the last 7 days of prices for each product on the front end - but store date for the last 30 days That full list should be downloadable to excel/csv We want a daily email alert showing the number of price changes / new products / removed products. I have a csv with the current SKUs and the current price, which we can use as a starting data point. Once up and running this scraper will need to sit on one of our servers Please ask any other questions you may have.

Data scraping

Data scraping for trades businesses (plumbers electricians etc) in Preston UK around a 10 mile radius

Python Web Scraping Expert Needed for UK Directory (42k Rows)

Description: We need a Python scraping expert to extract data from a public UK government directory (Architects Registration Board) mentioned below. https://architects-register.org.uk/ The Data: We need the full list of approximately 42,000 active architects. Fields required: Registration number, Name, Firm Name, Website, Address, Phone, Email, and Profile URL. The Technical Challenge: This site uses AJAX dynamic loading/session cookies. Standard visual scrapers (like ParseHub or WebHarvy) fail because the URL does not change on pagination. You will need to use a custom Python script (Selenium, Playwright, or Scrapy) to bypass the pagination block and extract the deep-click contact details. Requirements: Must be able to bypass AJAX pagination. Must deliver the final, clean Excel file within 48 hours of being hired. If you can deliver this quickly and cleanly, we have ongoing high-volume scraping projects for our enterprise clients.

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UK Business Data Scraping – Companies with 5–50 Employees

Description: I am looking for an experienced data scraping / lead generation specialist to build a high-quality list of UK businesses suitable for IT support services outreach. This data will be used for cold calling and email outreach by my internal sales team, so accuracy and relevance are extremely important. Target Businesses: - Location: United Kingdom - Company size: 5–50 employees Industries: Professional services, construction, property, finance, recruitment, logistics, healthcare clinics, legal firms, SMEs, etc. Exclude: IT companies, MSPs, software companies, telecom providers, public sector. Data Fields Required: For each company, I need: Company Name Contact Name (Owner / Director / IT Manager where possible) Job Title Phone Number (MAIN PRIORITY) Email Address (if available) Website Company Address / City Estimated Employee Size Industry / Sector LinkedIn Profile (company or contact if available) Volume Required: Initial test: 500 leads Ongoing potential: 2,000–5,000 leads per month if quality is good Data Sources (examples — open to suggestions): LinkedIn Google Maps Companies House Business directories Industry directories Public databases Important Requirements: Data must be GDPR compliant and sourced from publicly available information Phone numbers must be verified where possible No duplicate or low-quality records Prefer decision-maker contacts where available Deliverable Format: Excel or Google Sheets with clearly labelled columns. Ideal Freelancer: Proven experience with UK B2B lead generation Experience scraping LinkedIn and business directories Able to provide sample data before full project begins Good communication and reliability for ongoing work Please Include in Your Proposal: Examples of similar projects you’ve completed Your scraping tools / methods (VERY IMPORTANT) Cost per lead or cost per 500 leads Timeframe for delivery Sample (10–20 leads) if possible This may become a long-term ongoing project for the right person. Must be willing to negotiate on price, i've just set this price to speak to top certs but expecting a better price. Thank you.

Scrape comptitors website

I havea competitor " enchantedfairyportraits" whose website I would like to scrape and utilize on my website " fairyportriatstudio They have automation with emails etc

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1,000,000 UK business records scraped within 2 weeks 2

Hi there We need a database scraped of UK limited company names, their UK mobile number beginning 07, their email address, their website address, the Facebook business page URL and the link from where the details were obtained. The emails address needs to be generic such as info@businessname or hello@businessname We also need the category of industry from where each record relates to such as accountant, estate agent, clothes shop. We require 1,000,000 records within 2 weeks. If you are unable provide 1,000,000 in 2 weeks then please do not bid for the project. Please also do not bid on the project unless you have read the description and understand it completely. We have been contacted with numerous freelancers who state they can do it and then provide data which is nowhere near what we have asked for, so please, no time wasters. Thanks

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AI-Powered Price Scraper & Monitoring System (Multi-Website)

We are looking for an experienced developer to build a scalable AI-powered price scraping and monitoring system. The system should automatically extract product pricing data from multiple e-commerce websites and store it in a structured database for monitoring and analysis. The system must support multi-tenant architecture, role-based permissions, subscription tiers, and Stripe payment integration. The goal is to allow different companies to monitor product prices across multiple websites, with usage limits based on subscription plans. Project Scope 1. Target Websites • Scrape product prices from 7–10 e-commerce websites • Support dynamic content (JavaScript-rendered pages) • Proxy rotation & anti-bot handling • Scheduled scraping • Historical price tracking • Price change alerts (email or webhook) • Handle pagination and product variations 2. Multi-Tenant Architecture • Super Admin role • Manage all companies • Manage subscription plans • View system-wide usage • Suspend / activate companies 2. Data Extraction • Extract product name • Current price • Original price (if available) • SKU / Product ID • Availability status • Timestamp 3.1 Company Admin role • Manage company users • Set scraping targets (websites & products) • View company usage stats 3.2 Company Users • View price tracking dashboard • Access only assigned websites/products 3.3 Subscription & Usage Limits System must support different plan levels: Each plan should control: • Maximum number of websites • Maximum number of products • Scraping frequency (e.g., 1h / 3h / 6h / 24h) • Maximum concurrent scraping jobs • Historical data retention length Stripe Integration • Stripe subscription integration • Monthly / Yearly billing (7 days free trial) • Webhook handling for subscription status updates • Automatic feature unlock based on plan • Auto suspend account if payment fails • Admin ability to manually upgrade/downgrade plan 4. AI-Assisted Selector Detection • Use AI or intelligent selector logic to detect price elements • System should adapt if minor DOM changes occur • Minimize manual reconfiguration 5. Infrastructure • Proxy rotation support • Anti-bot handling • Headless browser support (e.g., Puppeteer / Playwright) • Scalable deployment (Docker preferred) 6. Database & Storage • Store data in MySQL • Historical price tracking • Ability to compare price changes 7. Monitoring & Automation • Scheduled scraping (e.g., every 1–6 hours) • Email or webhook alerts when price changes • Logging and error reporting 8. Dashboard • Admin and users dashboard • Search by product • View historical price chart Technical Requirements Preferred stack: • Laravel • Playwright / Puppeteer / Scrapy • REST API architecture • Docker deployment Deliverables • Fully working scraping system • Deployment guide • Source code • Documentation • 2 weeks post-delivery support Bonus Experience with anti-bot bypass, rotating residential proxies, and large-scale scraping is highly preferred. If interested, please include your portfolio and examples of similar scraping projects.

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1,000,000 UK business records scraped within 2 weeks

Hi there We need a database scraped of UK limited company names, their UK mobile number beginning 07, their email address, their website address, the Facebook business page URL and the link from where the details were obtained. The emails address needs to be generic such as info@businessname or hello@businessname We also need the category of industry from where each record relates to such as accountant, estate agent, clothes shop. We require 1,000,000 records within 2 weeks. If you are unable provide 1,000,000 in 2 weeks then please do not bid for the project. Thanks

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Python Data Pipeline — Web Scraping, Multi-Platform, languages

I'm building a children's activity discovery platform for Switzerland (think "Google for kids' activities"). I need a recurring data pipeline that scrapes class schedules from ~500 providers across multiple booking platforms in Geneva, expanding to all of Switzerland within 18 months. What needs to be scraped: Cogito-Sport (Angular/JavaScript portal) — 8-12 swimming clubs iClassPro (JavaScript portal) — 3-5 providers loisirsjeunes.ch (static HTML, paginated, ~200 activities via sequential IDs) Ville de Genève sports index (static HTML) PDF timetables (22 community centres) Individual club websites (mixed HTML) What to extract from each source: Activity name, provider, day of week, time, age range, price, address, registration URL. I'm building a children's activity discovery platform for Switzerland (think "Google for kids' activities"). I need a recurring data pipeline that scrapes class schedules from ~500 providers across multiple booking platforms in Geneva, expanding to all of Switzerland within 18 months. What needs to be scraped: Cogito-Sport (Angular/JavaScript portal) — 8-12 swimming clubs iClassPro (JavaScript portal) — 3-5 providers loisirsjeunes.ch (static HTML, paginated, ~200 activities via sequential IDs) Ville de Genève sports index (static HTML) PDF timetables (22 community centres) Individual club websites (mixed HTML) What to extract from each source: Activity name, provider, day of week, time, age range, price, address, registration URL. Deliverables: Working scrapers for all source types Config file to add new providers without code changes Normalisation layer mapping all sources to unified schema Change detection and summary email Deployment on Railway with cron schedule Clean CSV output + optional Airtable API push README written for non-developers In your proposal, briefly describe how you have handled JavaScript-rendered Angular or React pages in a previous project — what tools did you use and how did you handle DOM waiting? I have a full technical spec document available on request. P.S. Please note: due to payment processing limitations I am unable to work with freelancers based in Russia or Belarus.

Web Scraping Required

I require a structured data extraction project from the following directory: https://www.buildington.co.uk/companies The objective is to extract and structure company data into a clean Excel spreadsheet. Required fields: • Company Name • Contact Name (if available) • Telephone Number • Email Address • Website URL Important: • Some data is available directly on the directory page. • In certain cases, the freelancer may need to visit the company’s website to retrieve missing contact details. • Data must be structured, cleaned and deduplicated. • Output format: Excel (.xlsx) with clearly labelled columns. • Please confirm your approach and tools before starting. This is not a one-off copy and paste task. I am looking for someone who can create a reliable and efficient extraction method.